Prior art speech generation systems are not expandable in such a way as to allow non-expert administrators to expand the capability of the system. To the contrary, changes and modifications of prior art dialogue systems require significant engineering and developer resources and time. A general problem with goal-oriented dialogue systems, for example, that perform actions in the world (those that query APIs) is that they are bound by constraints on composition and predefined dialogue patterns. Compositionality is important to supporting rich functionality from a few primitives. However, to limit the combinatorial explosion when learning from weak supervision, constrained grammars are typically employed. This means that many meanings are simply not expressible. What is needed is an improved dialogue system that does not require significant engineering resources as in prior art systems when expanding.